THE ANGELO LAB
Stanford University
THE MICHAELANGELO LAB
THE MIBI TEAM
Mike Angelo, MD PhD
Principal Investigator
B.S. University of Mississippi
M.D. Ph.D. Duke University
Residency in Clinical Pathology, UCSF
mangelo0(at)stanford.edu
Mike's academic background spans across the fields of physics, biochemistry, electrical engineering, and medicine. During his residency he became interested in developing novel methods for immunohistochemical multiplexing using mass spectrometry leading to the development of MIBI during his postdoctoral work in the Nolan lab at Stanford University. Mike is now interested in optimizing MIBI and other mass reporter-based technologies further with the goal of identifying new transcriptional and translational signatures in solid tissue malignancies, and in allergic and other immunological disorders that can be used to improve clinical diagnosis and treatment
Staff
Marc Bosse, PhD
Senior Staff Scientist
B.Sc. Microbiology, University of Montreal
M.Sc. Microbiology & Immunology, University of Montreal
Ph.D. Experimental Medicine, Laval University, Canada
Postdoctoral fellow, Robarts Research Institute | Postdoctoral Fellow, SCC-RI, McMaster University
Research Area: Instrumentation and assay development
mbosse(at)stanford.edu
Marc has broad experience in microbiology, human stem cell biology and asthma research. He also worked in translational research developing a production process for an advance cell therapy product. He now works closely with Drs. Angelo and Bendall on improving MIBI technology. He is responsible for the maintenance of the MIBI-TOF imager and its day-to-day operation. He is also engaged in the development and adaption of molecular techniques for MIBI.
Ferda Filiz, MD
Staff Scientist
M.D. University of Genova School of Medicine
Residency in Pathology, Tulane School of Medicine and Danbury Hospital (Yale University School of Medicine affiliated program)
Research Area: Tissue pathology
ffiliz(at)stanford.edu
Ferda has nearly 12 years of industry experience where he worked as a pathologist in the clinical diagnostic division of Thermo Fisher Scientific handling IHC-related research. Ferda provides general assistance with tissue based (IHC) pathology related matters to graduate students and postdocs. He is involved in the oversight and management of our lab's contribution to the HuBMAP (Human BioMolecular Atlas Program) and CIMAC (Cancer Immune Monitoring and Analysis Centers) NIH/NCI funded consortium projects as well as the PICI (Parker Institute for Cancer Immunotherapy) glioblastoma multi-institute collaboration.
Xiaowei (Vivian) Lu, PhD
Staff Scientist
B.S. Pharmaceutical Sciences, Peking University Health Science Center, China
Ph.D. Chemistry, Michigan State University
Postdoctoral fellow, National Institute of Diabetes and Digestive and Kidney Diseases
Postdoctoral fellow, Medical University of South Carolina
Research Area: Imaging mass spectrometry of N-glycans in tissue, development of new analysis technologies for complex carbohydrates
xlu50020(at)stanford.edu
Xiaowei was initially trained as an organic carbohydrate chemist and worked for NIDDK for 5 years on carbohydrate vaccines. She then moved to imaging mass spectrometry area, doing organic and enzymatic reactions on glycans in FFPE tissue. Xiaowei is now responsible for the maintenance of the timsTOF flex MALDI-2. She is also engaged in method development on glycan imaging especially with the ion mobility function in the timsTOF.
Christine (Camacho) Fullaway
Life Science Technician II
B.S. Genetics, Molecular, & Cellular Biology, University of California, Davis
Research Area: QC development/optimization, research and project support
christinecamacho(at)stanford.edu
Christine has a broad range of research experience in industrial, academic and clinical lab settings. Her focus in the lab is streamlining and managing the upstream MIBI workflow (including both wet and dry lab work), developing and validating lab panels, and employing MIBI technology to validate QC methods in the lab. She also manages and supports other various aspects of the lab including ordering and chem safety management, as well as contributing to the wet lab work for specific projects. Her research interests include optimizing protocols to better fit the needs of the lab, as well as integrating computational tools and the MIBI to better understand the roles of various antibodies in a variety of diseases.
Mako Goldston
Life Science Technician I
B.S. Cell and Developmental Biology, University of California, Santa Barbara
Research Area: QC development/optimization, research support
makogold(at)stanford.edu
Mako is a recent graduate who is looking to explore and dive into the research world. Translational research has captured her interest due to its intersection between science and clinical care. She is particularly interested in Alzheimer’s pathology. Mako's role in the lab is to assist in different research projects and support the day to day operations of the lab, which includes quality control and validation of antibodies. Mako hopes to attend graduate school in the future.
Alex Kong
Computational Staff Scientist
B.S. Computer Science, University of California, Davis
M.S. Data Science, Columbia University
Research Area: Machine learning and computational analysis
alkong(at)stanford.edu
Alex received his BS computer science from the University of California, Davis and his MS in data science at Columbia University. He first became interested in working with medical data at ViDi Lab under Dr. Kwan-Liu Ma, where he developed analysis pipelines for patient vitals datasets. While at Columbia, Alex worked at INCITE under Dr. Peter Bearman, where he specialized in NLP and network analysis of university-level syllabi, mission statements, and application networks. Alex reached his goal of working in the medical field at Angelo Lab, where he is developing machine learning algorithms and analysis tools for MIBI-scanned data. In his spare time, Alex enjoys the piano, tennis, and hiking.
Sricharan Reddy Varra
Computational Staff Scientist
B.A. Computer Science, University of Colorado Boulder
Research Area: Machine learning and computational analysis
srivarra(at)stanford.edu
While at C.U Boulder, Sri gained an appreciation for computational and mathematical biology. During his time there, he collaborated with C.U.‘s UX team on applying quantitative methods for analyzing students’ reviews on their web portal. Sri is working towards developing image analysis tools for MIBI data, improving the existing software engineering pipelines, and improving the user experience. In my spare time, he enjoys cycling and creating digital 3D art.
Cami Sowers
Computational Staff Scientist
B.S. Applied Mathematics, University of California, Los Angeles
M.S. Mathematics, California State Polytechnic University, Pomona
Research Area: Computational analysis
csowers(at)stanford.edu
Cami received her BS in applied mathematics and computing from UCLA and then her MS in mathematics, with an emphasis in statistics, from Cal Poly Pomona. Completing her master’s thesis on COVID-19 data and interning at Berkeley Lab both sparked further interest in research and computational biology. Cami spends her time developing analysis tools for MIBI data.
Postdoctoral Fellows
Inna Averbukh, PhD
Postdoctoral Fellow, The Israel National Postdoctoral Award Program for Advancing Women in Science
B.Sc. Physics, The Technion - Israel Institute of Technology
B.Sc. Computer Science, The Technion - Israel Institute of Technology
M.Sc. Biological Physics, Weizmann Institute of Science, Israel
Ph.D. Biological Physics, Weizmann Institute of Science, Israel
Research Area: Maternal immune tolerance
innaa(at)stanford.edu
During Inna's PhD, she worked in the labs of Naama Barkai and Benny Shilo at the Weizmann Institute where she combined theoretical analysis with experimental validation to unravel the mechanisms responsible for robust patterning of embryos. In her post doc in the Itzkovitz lab at the Weizmann Institute, she combined single-cell RNA sequencing with spatial bulk transcriptomics to reconstruct a spatial atlas of gene expression by rare epithelial cells in the gut. In her current post doc in the Angelo lab, she is leveraging MIBI to explore spatio-temporal interactions at the maternal-fetal interface, which promotes maternal immune tolerance and successful pregnancy.
Rashmi Kumar, PhD
Postdoctoral Fellow
B.Sc. Chemistry, Presidency College, India
M.Sc. Organic Chemistry, Indian Institute of Technology Madras
Ph.D. Analytical-Organic Chemistry, Purdue University
Research Area: Methods development in MIBI, ductal cell carcinoma in situ
rashmi23(at)stanford.edu
It is widely accepted that genomic changes in DNA and RNA are often major drivers of cancer progression. However, very few methods exist where protein epitopes and DNA and/or RNA can be detected simultaneously. Rashmi is developing in-situ hybridization techniques such that RNA transcripts and chromosomal copy numbers can be detected using multiplexed ion beam imaging mass spectrometry. Using these techniques, she plans to explore copy number alterations associated with risk stratification and invasiveness of DCIS. These techniques will also allow identification of genomic drivers responsible for phenotypic variation in tumor-immune microenvironment.
Hadeesha Piyadasa, PhD
Postdoctoral Fellow, Canadian Institutes of Health Research Fellowship
Co-advisor: Dr. Sean Bendall
B.Sc. Biochemistry, University of Manitoba, Canada
Ph.D. Immunology, University of Manitoba, Canada
Research Area: Glial tumor microenvironment in response to immunotherapy
piyadasa(at)stanford.edu
Hadeesha completed his PhD at the University of Manitoba (Dr. Neeloffer Mookherjee’s lab) where he used animal models and multiomic approaches to study the use of synthetic immunoregulatory peptides in airway inflammation. For his postdoc at the Angelo and Bendall lab, he is leveraging MIBI to generate a comprehensive understanding of the TME and the antigenic heterogeneity of glial tumors from pediatric and adult patients in response to conventional, vaccine, checkpoint inhibitor, and cellular therapies.
Graduate Students
Erin McCaffrey
Graduate Student, Immunology, NSF Fellowship
B.S. Microbiology, University of Maryland-College Park
Research Area: Tuberculosis and granulomatous diseases
erinmcc(at)stanford.edu
During her undergraduate work in microbiology Erin became interested in the complex immune-evasion strategies of M. tuberculosis (TB) and its massive global burden in underserved patient populations. Her work focuses on elucidating immune mechanisms within TB granulomas that may drive disparate clinical outcomes. She is employing MIBI to identify immune cell populations, define their phenotypes, and asses their histologic organization within granulomas across the disease spectrum of TB in both human and non-human primate models of infection.
Noah Greenwald
Graduate Student, Cancer Biology, Stanford Graduate Fellowship, NIH F31 Fellowship, NIH F99/K00 Fellowship
Co-Advisor: Dr. Christina Curtis
B.A. Biophysics, Harvard University
Research Area: Computational image analysis and cancer biology
nfgreen(at)stanford.edu
Noah received his BA in Biophysics from Harvard University. He then worked for two years at Harvard Medical School and the Broad Institute in the labs of Drs. Rameen Beroukhim and Ian Dunn studying the genomics of brain tumors. Noah is interested in combining multiplexed imaging techniques with genomics to understand the tumor microenvironment and response to therapy. He also works on developing tools for cell segmentation and computational analysis.
Candace Liu
Graduate Student, Immunology, Stanford Graduate Fellowship, NIH F31 Fellowship
B.S. Chemical & Biomolecular Engineering, Johns Hopkins University
Research Area: Computational image analysis and HIV
cliu72(at)stanford.edu
After finishing her undergraduate degree at Johns Hopkins, Candace worked at the National Institutes of Health for two years in the Laboratory of Immune System Biology under Dr. John Tsang, where she became interested in systems immunology and computational biology. She is interested in combining MIBI with genomics and/or epigenomics data to study latent viral reservoirs in HIV infection. She is also interested in building machine learning tools for image analysis.
Erin Soon
Graduate Student, Immunology, National Science Scholarship, A*STAR
B.Sc. Pharmacology, Imperial College London
Research Area: Placenta immunobiology
erinsoon(at)stanford.edu
Erin first became interested in fetal immunology while working with Florent Ginhoux at the Singapore Immunology Network during her undergraduate days. She subsequently dabbled in translational immunotherapy for chronic wounds and zebrafish genetics before deciding that she wanted to return to exploring the immune interactions at play during pregnancy. She is leveraging MIBI and complementary single cell analyses to interrogate the mechanisms of immune tolerance at the maternal-fetal interface.
Ke Leow
Graduate Student, Cancer Biology, National Science Scholarship, A*STAR
B.Sc. in Biochemistry, Imperial College London
Research Area: Post-translational modifications and cancer biology
kxleow(at)stanford.edu
Through her undergraduate studies in Imperial College London, Ke found strong interest in systems biology and omics technologies. She performed mass spectrometry analysis of glycans in human platelets during her final year project in Dr Anne Dell’s and Dr Stuart Haslam’s lab. Then, she worked for a year in the metabolomics group at Bioprocessing Technology Institute in Singapore. Ke is now interested in studying the effects of glycosylation on cancer immunotherapy using MIBI. She also hopes to develop tools for imaging glycoproteins.
Alea Delmastro
Graduate Student, Immunology
Co-Advisor: Dr. Prasanna Jagannathan
B.S. Chemical Engineering, Stanford University
M.S. Biomedical Informatics, Stanford University
Research Area: Malaria in pregnancy
alead(at)stanford.edu
Alea is interested in studying infectious disease, specifically relating to malaria. In malaria-endemic settings, pregnant women are highly susceptible to severe Plasmodium falciparum (Pf) infection, which can result in placental malaria as well as adverse birth outcomes. Utilizing multiplexed ion beam imaging and other single cell methods, Alea aims to characterize the immune cell infiltrate during placental malaria and better understand the response to Pf at the maternal-fetal interface.
Potchara Boonrat
Graduate Student, Immunology, Baker International Fellowship, Anandamahidol Foundation Scholarship
B.Sc. Biology, Chulalongkorn University
Research Area: Tuberculosis
potchara(at)stanford.edu
Potchara earned his B.Sc. in Biology from Chulalongkorn University where he worked on the development of chimeric antigen receptor (CAR) T cells for Epstein-Barr virus-related cancers. During his undergraduate studies, he became interested in how pathogens evade the immune system. Potchara is currently employing MIBI to investigate the mechanism of Mycobacterium tuberculosis (TB)-mediated immune tolerance in the lymph node.
Cameron Walker
Graduate Student, Cancer Biology
B.Sc. Biomedical Engineering, Duke University
M.S. Bioengineering, UC San Diego
Research Area: Tumor immunology, metastasis
cwalker8(at)stanford.edu
Cameron completed his BSc in Biomedical Engineering from Duke University and his MS in Bioengineering from UC San Diego. After graduating, Cameron began working at a clinical stage immunotherapy start-up, where he developed a passion for understanding the mechanisms by which cancer evades immune detection. He is currently employing MIBI and other single cell methods to examine the local and systemic immunological effects of lymph node metastasis.
Lorenz Rumberger
Visiting Student Researcher, Charité University Hospital | Max Delbrück Center for Molecular Medicine, Berlin
B.Sc Economics, Hamburg University
M.Sc. Information Systems, Humboldt University Berlin
Research Area: Computational image analysis and cancer biology
jlrumber(at)stanford.edu
After finishing his masters degree at Humboldt University, Lorenz started as a PhD Candidate in the CompCancer Graduate School and Dagmar Kainmuellers Lab at Max Delbrück Center. He works on computational methods for pathology image analysis to better understand the effects of spatial heterogeneity on clinical outcomes of cancer. During his visit in our Lab, he develops computational tools for our multiplexed image analysis pipeline.